The present invention relates to adaptive filtering, and more particularly, to adaptive filtering of medical images for simultaneous noise reduction and structure enhancement.
Adaptive filtering in image processing refers to self-adapting methods which adjust intensities of pixels in an image by integrating and weighting the intensities of neighboring pixels according to local structures in the image. Such methods may be used in medical imaging to improve image quality of raw image data. In order to improve image quality in medical images, it is desirable to mitigate noise resulting from image acquisition devices and to simultaneously enhance important structures in the medical images. It is important that adaptive filtering techniques completely preserve diagnostic patterns or structures in an image without generating artifacts or noise of any kind due to the filtering process, so that no pathological information is lost or created in the image.
Many convention adaptive filtering techniques utilize edge preserving noise suppression, or so-called “denoising” methods. Such denoising methods include, wavelet coefficient thresholding/shrinkage, variational methods, Bayesian framework with Markov random filed model, and bilateral filtering. However, while these methods are capable of reducing noise in images, they do not enhance structures in the images. Although methods have been introduced for simultaneous noise reduction and structure enhancement, these methods are either unsuitable for medical applications or too computationally intensive to meet real-time requirements.